The fields of ocular surgery, virtual environment technology, autonomous driving, robotic localization, and inertial localization are experiencing significant advancements, driven by the development of innovative methods and techniques. A common theme among these areas is the increasing emphasis on precision, efficiency, and adaptability. Researchers are exploring new approaches to improve the accuracy and robustness of sensing and perception systems, including the use of deep learning frameworks, sensor fusion, and probabilistic methods. Notable progress has been made in monocular depth estimation, 3D lane detection, and visual place recognition, with state-of-the-art performance achieved in various benchmarks. The development of new benchmarks and evaluation protocols is also an active area of research, with a focus on assessing the practical utility of foundation models in real-world applications. Furthermore, the importance of ethical decision-making and human-machine collaboration is being highlighted, with researchers investigating ways to integrate human values and preferences into autonomous systems and create seamless interactions between humans and machines. Overall, the convergence of emerging technologies in sensing, perception, and autonomous systems is expected to have a significant impact on various industries and applications, including healthcare, transportation, and robotics.